High fireline intensities can trigger fire-atmosphere interaction, producing more extreme and often unexpected fire behavior. These fire-line intensities have been enhanced in recent decades by the increase in fuel load (Di Virgilio et al., 2019;Ruffault et al., 2018;Turco et al., 2018) after changes in landscape management (Pyne, 2019) and by climate change-driven aridity (Abatzoglou et al., 2019). The resulting extreme wildfires are overwhelming fire service operational capacity and becoming a new normal (Jolly et al., 2015), even with reinforced efforts and advanced technologies. The increase in extreme wildfires has had an impact on a global scale, resulting in dramatic consequences in terms of human lives: 173 deaths in Australia in 2009; 110 deaths between June and
The natural regeneration of ecosystems impacted by fires is a high priority in Bolivia, and represents one of the country’s greatest environmental challenges. With the abundance of spatial data and access to improved technologies, it is critical to provide an effective method of analysis to evaluate changes in land use in the face of the global need to understand the dynamics of vegetation in regeneration processes. In this context, we evaluated the dynamics of natural regeneration through phenological patterns by measuring the maximal and minimal spectral thresholds at four fire-impacted sites in Chiquitania in 2019 and 2020, and compared them with unburned areas using harmonic fitted values of the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR). We used two-way ANOVA test to evaluate the significant differences in the values of the profiles of NDVI and NBR indices. We quantified severity at the four study sites using the dNBR obtained from the difference between pre- and postfire NBR. Additionally, we selected 66 sampling sites to apply the Composite Burn Index (CBI) methodology. Our results indicate that NBR is the most reliable index for interannual comparisons and determining changes in the phenological pattern, which allow for the detection of postfire regeneration. Fire severity levels based on dNBR and CBI indices are reliable methodologies that allow for determining the severity and dynamics of changes in postfire regeneration levels in forested and nonforested areas.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.